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Tech Stack
Tools & technologiesPythonScikit-LearnSQLTableau
About the role
Key responsibilities & impact- Build and maintain predictive models that drive marketing strategy, including player LTV, churn risk, CAC payback, and propensity-to-convert models
- Own marketing attribution and incrementality analysis across paid channels (Meta, Google, TikTok, affiliates, influencers, etc.), helping the team understand what's actually driving growth
- Quantify the causal impact and long-term business value of promotions, bonuses, and lifecycle campaigns, moving beyond surface-level engagement metrics to measure true incremental retention, monetization, and LTV impact
- Apply causal inference techniques (geo experiments, synthetic control, diff-in-diff, CausalImpact, uplift modeling) to evaluate marketing investments where clean A/B tests aren't possible
- Partner with growth marketers to design, run, and read out experiments: A/B tests, geo-tests, holdout studies, and creative tests
- Develop and maintain dashboards and self-serve reporting that give marketing leaders real-time visibility into channel performance, cohort behavior, promo ROI, and funnel health
- Clean, structure, and validate data across our marketing stack (ad platforms, MMP, internal event data, CRM) and partner with data engineering to improve our data models where needed
- Translate complex analyses into clear, actionable recommendations for non-technical stakeholders
- Continuously look for opportunities to automate, improve, and scale how the marketing team uses data
Requirements
What you’ll need- 5+ years of experience as a data scientist, marketing analyst, or growth analyst, ideally in a consumer app, gaming, fintech, or subscription business
- Strong SQL skills and comfort working with large, messy behavioral datasets
- Hands-on experience building predictive models in Python (LTV, churn, propensity, segmentation, etc.) using libraries like scikit-learn, XGBoost, or similar
- Experience evaluating the long-term and incremental impact of marketing and promotional spend: you understand the difference between *who responded* and *who was actually influenced*
- Working knowledge of causal inference methods (diff-in-diff, synthetic control, CausalImpact, uplift modeling, propensity scoring) and when to apply each
- Solid grounding in marketing measurement concepts: attribution (MTA, MMM basics), incrementality, holdouts, cohort analysis, and unit economics (CAC, LTV, payback)
- Experience with experimentation: designing tests, sizing them, and reading them out with statistical rigor
- Proficiency with at least one BI/visualization tool (Looker, Tableau, Mode, Sigma, etc.)
- Strong communication skills: you can explain a model to a marketer and a campaign result to a CFO with equal clarity
- A bias toward action: you'd rather ship a useful 80% answer this week than a perfect one next quarter
Benefits
Comp & perks- Competitive compensation package, including base salary, benefits, and equity.
- Unlimited/Flexible paid time off.
- Health benefits, including medical, dental, and vision coverage, as well as generous parental leave.
- Employee-sponsored 401(k).
- $500 work-from-home stipend + Equipment & Accessories.
- Work Remotely.
- Opportunity for professional development in a dynamic, global setting.
- A supportive, collaborative, and knowledge-driven workplace. An engaging and challenging role with the freedom to innovate and develop effective solutions.
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
predictive modelingcausal inference techniquesA/B testingSQLPythonscikit-learnXGBoostmarketing measurementincrementality analysiscohort analysis
Soft Skills
strong communicationaction-orientedanalytical thinkingcollaborationproblem-solvingdata storytellingstakeholder engagementadaptabilityattention to detailcreativity